DOI QR코드

DOI QR Code

The Insights of Localization through Mobile Anchor Nodes in Wireless Sensor Networks with Irregular Radio

  • Han, Guangjie (Department of Information & Communication Systems, Hohai University) ;
  • Xu, Huihui (Department of Information & Communication Systems, Hohai University) ;
  • Jiang, Jinfang (Department of Information & Communication Systems, Hohai University) ;
  • Shu, Lei (College of Electronic Information and Computer, Guangdong University of Petrochemical Technology) ;
  • Chilamkurti, Naveen (Department of Computer Science and Computer Engineering, La Trobe University)
  • Received : 2011.09.19
  • Accepted : 2012.11.13
  • Published : 2012.11.30

Abstract

Recently there has been an increasing interest in exploring the radio irregularity research problem in Wireless Sensor Networks (WSNs). Measurements on real test-beds provide insights and fundamental information for a radio irregularity model. In our previous work "LMAT", we solved the path planning problem of the mobile anchor node without taking into account the radio irregularity model. This paper further studies how the localization performance is affected by radio irregularity. There is high probability that unknown nodes cannot receive sufficient location messages under the radio irregularity model. Therefore, we dynamically adjust the anchor node's radio range to guarantee that all the unknown nodes can receive sufficient localization information. In order to improve localization accuracy, we propose a new 2-hop localization scheme. Furthermore, we point out the relationship between degree of irregularity (DOI) and communication distance, and the impact of radio irregularity on message receiving probability. Finally, simulations show that, compared with 1-hop localization scheme, the 2-hop localization scheme with the radio irregularity model reduces the average localization error by about 20.51%.

Keywords

Cited by

  1. An Efficient Distributed Trust Model for Wireless Sensor Networks vol.26, pp.5, 2015, https://doi.org/10.1109/tpds.2014.2320505
  2. A Location Prediction Algorithm with Daily Routines in Location-Based Participatory Sensing Systems vol.11, pp.10, 2015, https://doi.org/10.1155/2015/481705
  3. Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial vol.11, pp.3, 2012, https://doi.org/10.1109/jsyst.2015.2434822